Code Division Multiple Access (CDMA) has been extensively used in such areas as cellular and satellite communications. CDMA signals increase the spectrum required for the transmission of a particular data rate, by modulating each information symbol with a spread spectrum code having a rate larger than the data rate. In CDMA systems, the same spreading code is used for each information symbol. Typically, the spreading code is comprised of several tens or a few hundred elements, called chips. To decrease the correlation among spreading codes assigned to different system users, and thereby reduce the interference among the different users, the data stream after having been spread is typically scrambled with a pseudonoise (PN) code that is generated serially and cyclically and has a larger period than the spreading code. Examples of such CDMA signal spreading schemes are the schemes used by the IS-95/CDMA2000 and 3GPP (Third Generation Partnership Project) communication standards.
In the forward link of CDMA cellular communication systems, i.e. the communication link from base stations to mobile terminals (also referred to as user equipment (UE) or devices); the wireless channel may introduce multipath propagation. Even if the signals transmitted by the base station are spread using orthogonal codes (e.g., Walsh codes), the multipath propagation may destroy the orthogonality and produce multiple-access interference (MAI).
Typically, the forward link also includes a common pilot channel (CPICH) that carries known data and can be decoded by all mobiles. The CPICH is intended to provide channel information in order to enable the mobile receiver to identify received signal paths, estimate the channel, and perform tracking functions such as time and frequency tracking. Examples of CDMA communication system including a CPICH are encountered in 3GPP Release 1999 and Release 5 and in CDMA-2000 and 1xEVDV.
If the forward link does not employ transmit diversity, then an identical channel is experienced by the desired signal and the remaining same-cell interfering signals. For systems employing orthogonal spreading codes, such as the 3GPP Release 1999, 3GPP Release 5, and CDMA 2000, 1xEVDV standard compliant systems, chip equalization can restore orthogonality even in the presence of a scrambling code with a period much longer than the one for the orthogonal code (long scrambling code).
Several channel equalization methods have been proposed in the literature, including a least-mean-squares (LMS) algorithm approach [1] (Visotsky, et al, U.S. Pat. No. 6,175,588, Jan. 16, 2001), a Prefilter Rake receiver approach [2] (Heikkilae and Komulainen, WO0054427, Sep. 14, 2000), a Griffiths equalizer approach [3] (Heikkila, “A Novel Blind Adaptive Algorithm for Channel Equalization in WCDMA Downlink”, pages A-41-A-45, Personal, Indoor and Mobile Radio Communications (PIMRC) 2001), and the conventional least-minimum-mean-squared-error (LMMSE) algorithm. All aforementioned equalizers, with the exception of LMMSE, are adaptive. The Prefilter Rake and Griffiths equalizers use an adaptation method that is similar in structure with that of the LMS. The advantage of such LMS-type algorithms is that the associated complexity is linear with the equalizer length.
The attractive feature of the CPICH-based LMS equalizer in [1] is its robustness to realistic imperfections. Channel estimation is not required and, since the CPICH-based LMS uses a single training signal, the actual multi-path profile is not relevant to the operation of the equalizer. The drawback of the CPICH-based LMS is its slow convergence in fast fading channel situations and its poor performance in the case of a weak training signal situation. Typically, the CPICH contains only about 10% of the total transmitted power and consequently the CPICH-based LMS equalizer in [1] uses only a small portion of the transmitted power. The result may be slow and inefficient adaptation, particularly in difficult channel conditions such as those encountered in rich multipath environments with high mobile speeds. As a consequence, the CPICH-based LMS may significantly under perform other linear complexity equalizers and it may not always offer better performance than the conventional Rake receiver that attempts no interference suppression.
The Prefilter Rake and Griffiths equalizers need channel estimation and are sensitive to time errors, relative path separation and unrecovered multipath power. These equalizers need to identify all existing paths and place a Rake finger at their time arrival instance (Prefilter Rake) or use the estimated channel response to adaptively invert the channel effect (Griffiths). Time errors affect the performance because of imperfect equalization. Path separation affects the performance in a similar fashion as time errors since a Rake finger needs to be placed at the correct time arrival of each path. Because paths arrive at arbitrary time instants, the time resolution needs to be at sub-chip level. Since the equalizer needs to span the entire delay spread of the channel in order to equalize all existing paths, the requirement for time resolution finer than 1 chip implies that the equalizer length has to be at least twice as long as the length of an equalizer requiring chip-spaced signal samples. A consequence of the previous requirement is that the convergence and adaptation of the equalizers will be slower as a result of the longer length and sub-chip signal samples. This leads to performance degradation. Another consequence is the associated increase in complexity due to the increased equalizer length. Finally, if there are paths that cannot be identified by the equalizer, either because they are too close (less than 1 chip apart) to an existing stronger path or because they are too weak to be identified, they will not be equalized and constitute interference. This can be especially harmful to interference sensitive modulations such as QAM-type and M-PSK-type (for M larger than 4) modulations. None of the previous shortcomings of Prefilter Rake and Griffiths equalizers is an issue for adaptive equalizers using a training signal for adaptation, such as the CPICH-based LMS equalizer in [1] or the LMS equalizer with decision feedback disclosed in this invention.
The LMMSE technique has the potential to provide the best performance at the expense of very high computational complexity. The channel estimate for each multipath is needed and the inversion of the associated channel response covariance matrix needs to be typically performed at the rate of channel estimation updates. However, this matrix may not always be invertible, particularly in independently fading multipath channels. A consequence of this effect is that the channel response covariance matrix needs to span a much larger duration than the one defined by the separation in samples between the first and last arriving paths as they are identified at the receiver. Since the multipath delay spread may be in the order of tens of chip periods, the channel response covariance matrix dimension may well exceed 100 in order to ensure a large enough probability for its invertibility. The larger the matrix dimension, the larger the probability that the matrix will be invertible at all time instances. Moreover, the LMMSE suffers from the same drawbacks previously mentioned for the Prefilter Rake and Griffiths equalizers. The complexity and sensitivity of the LMMSE to realistic imperfections severely diminish its usefulness as a channel equalizer for spread spectrum signals.
A general structure for a prior art chip equalizer is shown in FIG. 1. The received signal 102 is passed through the LMS equalizer 104 to produce the equalizer output 106. Using the spreading (Walsh) and scrambling (PN) codes 108, the CPICH signal 110 is generated and subtracted from the equalizer output to generate the error signal 112 which is then used to train the equalizer. The equalizer output 106 is also passed through despreader 114 to produce the decision statistic output 116.
The objective in developing channel equalizers for the forward link of CDMA systems naturally concentrates on improving the performance and tracking ability of the CPICH-based LMS technique and on approaching the performance theoretically achievable using the LMMSE. Moreover, robustness to realistic imperfections is necessary in order to avoid the limitations of the Prefilter Rake and Griffiths equalizers. Given the above shortcomings of present art equalizers, a need exists in the art for a method and apparatus that can restore orthogonality and suppress interference in the forward link of a CDMA communication system while having low complexity, achieving better performance than the conventional Rake receiver, and offering robust performance under realistic setups and imperfections of the communications link.